Ordered Random Variables from Discontinuous Distributions

Distributions of Ratios: From Random Variables to Random Matrices

The ratio R of two random quantities is frequently encountered in probability and statistics. But while for unidimensional statistical variables the distribution of R can be computed relatively easily, for symmetric positive definite random matrices, this ratio can take various forms and its distribution, and even its definition, can offer many challenges. However, for the distribution of its d...

Random Variables , Distributions and Expectation 1 Random Variables

We’ve used probablity to model a variety of experiments, games, and tests. Throughout, we have tried to compute probabilities of events. We asked, for example, what is the probability of the event that you win the Monty Hall game? What is the probability of the event that it rains, given that the weatherman carried his umbrella today? What is the probability of the event that you have a rare di...

Random Variables and Their Distributions

Contents 1. Introduction. 2. The distribution function of a random variable. 3. Classification of random variables. 4. Some special discrete probability distributions. 5. Some special continuous probability distributions. 6. Location characteristics of a real-valued random variable. 7. Dispersion characteristics of a real-valued random variable. 8. Joint distribution functions. 9. Independence ...

Distributions of Functions of Normal Random Variables

The unit or standard normal random variable U is a normally distributed variable with mean zero and variance one, i. e. U ∼ N(0, 1). Note that if x ∼ N(µ, σ 2) that x − µ σ ∼ U ∼ N(0, 1) (1) Thus to simulate a normal random variable with mean µ and variance σ 2 , we can simply transform unit normals, as x ∼ µ + σU ∼ N(µ, σ 2) (2) Consider n independent random variables x i ∼ N(µ, σ 2), then x ∼...

Distributions of Functions of Normal Random Variables

Random Variables, Distributions, and Expected Value

1. A random variable is a variable that takes specific values with specific probabilities. It can be thought of as a variable whose value depends on the outcome of an uncertain event. 2. We usually denote random variables by capital letters near the end of the alphabet; e.g., X,Y,Z. 3. Example: Let X be the outcome of the roll of a die. Then X is a random variable. Its possible values are 1, 2,...